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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ab Initio Limits of Atomic Nuclei

We predict the limits of existence of atomic nuclei, the proton and neutron drip lines, from the light through medium-mass regions. Starting from a chiral two- and three-nucleon interaction with good saturation properties, we use the valence-space in-medium similarity renormalization group to calculate ground-state and separation energies from helium to iron, nearly 700 isotopes in total. Here, we use the available experimental data to quantify the theoretical uncertainties for our ab initio calculations towards the drip lines. Where the drip lines are known experimentally, our predictions are consistent within the estimated uncertainty. For the neutron-rich sodium to chromium isotopes, we provide predictions to be tested at rare-isotope beam facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Ab initio quantum scattering calculations for the CO–O 2 system and a new CO–O 2 potential energy surface: O 2 and air broadening of the R(0) line in CO

We present ab initio calculations of the collisional broadening of the R(0) pure rotational line in CO (at 115 GHz) perturbed by O 2 . Our calculations are done in a fully quantum way by solving close-coupling quantum-scattering equations without any approximations. We also report a new, highly accurate CO–O 2 potential energy surface on which we did the quantum-scattering calculations. The calculated collisional broadening agrees with the available experimental data in a wide temperature range. The calculated collisional shift is negligible compared to the broadening, which is also consistent with the experimental data. We combine this result with our previous calculations for the same line in CO perturbed by N 2 [Józwiak et al., J. Chem. Phys. 154, 054314 (2021)]; the obtained air-perturbed broadening of the R(0) pure rotational line in CO and its temperature dependence perfectly agree with the HITRAN database. This result constitutes an important step toward developing a methodology for providing accurate ab initio reference data on spectroscopic collisional line-shape parameters for molecular systems relevant to the Earth’s atmosphere and for populating spectroscopic line-by-line databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Extracting the number of short-range correlated nucleon pairs from inclusive electron scattering data

The extraction of the relative abundances of short-range correlated (SRC) nucleon pairs from inclusive electron scattering is studied using the generalized contact formalism (GCF) with several nuclear interaction models. GCF calculations can reproduce the observed scaling of the cross-section ratios for nuclei relative to deuterium at high xB and large Q 2 , a 2 =(σ A /A)/(σ d /2). In the nonrelativistic instant-form formulation, the calculation is very sensitive to the model parameters and only reproduces the data using parameters that are inconsistent with ab initio many-body calculations. Using a light-cone GCF formulation significantly decreases this sensitivity and improves the agreement with ab initio calculations. The ratio of similar mass isotopes, such as 40 Ca and 48 Ca, should be sensitive to the nuclear asymmetry dependence of SRCs, but is found to also be sensitive to low-energy nuclear structure. Thus the empirical association of SRC pair abundances with the measured a2 values is only accurate to about 20%. Finally, improving this will require cross-section calculations that reproduce the data while properly accounting for both nuclear structure and relativistic effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides

Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗
DOE OSTI2021

Ultra-large-scale ab initio quantum chemical computation of bio-molecular systems: The case of spike protein of SARS-CoV-2 virus

The COVID-19 pandemic poses a severe threat to human health with an unprecedented social and economic disruption. Spike (S) glycoprotein of the SARS-CoV-2 virus is pivotal in understanding the virus anatomy, since it initiates the first contact with the ACE2 receptor in the human cell. We report results of ab initio computation of the spike protein, the largest ab initio quantum chemical computation to date on any bio-molecular system, using a divide and conquer strategy by focusing on individual structural domains. In this approach we divided the S-protein into seven structural domains: N-terminal domain (NTD), receptor binding domain (RBD), subdomain 1 (SD1), subdomain 2 (SD2), fusion peptide (FP), heptad repeat 1 with central helix (HR1-CH) and connector domain (CD). The entire Chain A has 14,488 atoms including the hydrogen atoms but excluding the amino acids with missing coordinates based on the PDB data (ID: 6VSB). The results include structural refinement, ab initio calculation of intramolecular bonding mechanism, 3- dimensional non-local inter-amino acid interaction with implications for the inter-domain interaction. Details of the electronic structure, interatomic bonding, partial charge distribution and the role played by hydrogen bond network are discussed. In the interaction among structural domains, we present new insights for crucial hinge-like movement and fusion process. Extension of such calculation to the interface between the S-protein binding domain and ACE2 receptor can provide a pathway for computational understanding of mutations and the design of therapeutic drugs to combat the COVID-19 pandemic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Halo effective field theory analysis of one-neutron knockout reactions of Be 11 and C 15

Background: One-nucleon knockout reactions provide insightful information on the single-particle structure of nuclei. When applied to one-neutron halo nuclei, they are purely peripheral, suggesting that they could be properly modeled by describing the projectile within a halo effective field theory (halo-EFT). Purpose: We reanalyze the one-neutron knockout measurements of 11 Be and 15 C —both one-neutron halo nuclei—on beryllium at about 60 MeV/nucleon. We consider halo-EFT descriptions of these nuclei which already provide excellent agreement with breakup and transfer data. Method: Here we include a halo-EFT description of the projectile within an eikonal-based model of the reaction and compare its outcome to existing data. Results: Excellent agreement with experiment is found for both nuclei. The asymptotic normalization coefficients inferred from this comparison confirm predictions from ab initio nuclear-structure calculations and values deduced from transfer data. Conclusions: Halo-EFT can be reliably used to analyze one-neutron knockout reactions measured for halo nuclei and test predictions from state-of-the-art nuclear structure models on these experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗
DOE OSTI2018

Analytic model of the γ -surface deviation and influence on the stacking fault width between partial dislocations

The stacking fault width (R$_{eq}$) between partial dislocations within an FCC crystalline lattice characterizes the onset of numerous plastic flow mechanisms, as well as the relationship between material strength and grain size. Continuum models traditionally consider a complete unit of dislocation slip ( b ) along the $\langle{110}$$\rangle$ direction distributed between two discrete partial dislocations, each with a fixed partial Burgers vector ( b p ), which bound a stacking fault. Across the stacking fault, the vectorial slip is assumed to be constant, yielding a constant intrinsic stacking fault energy density, $\gamma$$_{isf}$ Here, we demonstrate that the vectorial displacement path taken in accomplishing a complete unit of slip (b) deviates from the expected displacement path containing the local minima, $\gamma$$_{isf}$ leading to a correction in the nominally derived stacking fault width. The magnitude of the correction depends on both the net orientation of the dislocation within the lattice, and also the degree of relaxation of each partial Burgers vector along the $\langle{\bar{1}12}$$\rangle$ direction. We derive a simple analytic model for the corrected stacking fault width, explicitly accounting for the deviation, by introducing a variable ξ (0 < ξ < 1), which governs the magnitude of each partial dislocation component along the $\langle{\bar{1}12}$$\rangle$ direction. Significantly, our model predicts a correction to R$_{eq}$ of ~$\mathscr{O}$ (|b|) for the nominally screw dislocation, and has no noticeable influence on nominally edge dislocations. We apply our model towards computing the stacking fault width of several FCC metals, and demonstrate excellent agreement both with our own numerical data as well as that obtained from ab initio and Molecular Statics (MS) methods within the literature. Lastly, the results from this study demonstrate that, upon judicious application, discrete linear elastic models are successful in reproducing elastic interactions as computed from higher fidelity models on the spatial scale of metallic dislocation cores.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Correlated Displacement of Dynamic Elastic Dipoles Produces Nonclassical Electrostriction in Zr-Doped Ceria

By combining experimental data with density functional theory-based ab initio molecular dynamics modeling, this work provides evidence that nonclassical electrostriction in isovalent Zr-doped ceria is due to the correlated anharmonic motion of dynamic elastic dipoles associated with multiple [ZrO 8 ]-local bonding units with a high Zr concentration (Zr 0.1 Ce 0.9 O 2 ). Introduction of 0.5 mol % trivalent or divalent codopants (Sc, Yb, La, or Ca) reduces the longitudinal electrostriction strain coefficient by more than a factor of 10, produces a 3-fold decrease in the relative dielectric permittivity, and increases the elastic modulus. Since these changes depend neither on the radius nor on the valency of the codopant, we conclude that the responsible species are charge-compensating oxygen vacancies (VO). For trivalent dopants (Do 0.005 Zr 0.1 Ce 0.895 O 1.9975 ), oxygen vacancies are present at a concentration ratio 1:40 with respect to Zr, giving, for random distribution, a characteristic interaction distance of ≤2.3 unit cells (1.2 nm). Oxygen vacancies participate in [ZrO 7 -V O ] local bonding units, disrupting the correlated dynamic displacements of the connected [ZrO 8 ]-local bonding units. Finally, such correlated motion of dynamic elastic dipoles may also explain the exponential increase in the longitudinal electrostriction strain coefficient with an increase in Zr concentration to <0.2 mole fraction and must be taken into account for further development of nonclassical electrostrictors based on Zr-doped ceria.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing High-Temperature Amine Chemistry: Is the Reaction NH 3 + NH 2 ⇌ N 2 H 3 + H 2 Important?

The reaction NH 3 + NH 2 ⇌ N 2 H 3 + H 2 (R1) has been identified as a key step to explain experimental results for pyrolysis and oxidation of ammonia. However, no direct experimental or theoretical evidence for the reaction has been reported. In the present work, the reaction was studied by ab initio theory and by reinterpretation of experimental data. We could not locate a transition state for R1 occurring as a direct process, but alternative mechanisms yielded an upper bound to k 1 of 1.5 × 10 13 exp(–58.9 kcal mol –1 /RT) cm 3 mol –1 s –1 over 1000–2500 K, several orders of magnitude lower than values applied in modeling. Consistent with the theoretical work, re-evaluation of NH 3 pyrolysis data supported a very low value of k 1 . However, this finding opens up a novel unresolved issue. Current kinetic models cannot capture the NH 3 oxidation behavior in a number of laminar flow reactor and jet-stirred reactor experiments without adopting an improbably high value for k 1 . Furthermore, important oxidation steps might be underestimated or missing from mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Structural and Dynamic Heterogeneity of Deep Eutectic Solvents Composed of Choline Chloride and Ortho-Phenol Derivatives

Structural, thermal, and dynamic properties of four deep eutectic solvents comprising choline chloride paired with ortho-phenolic derivative hydrogen-bond donors were probed using experiments and molecular simulations. The hydrogen-bond donors include phenol, catechol, o-chlorophenol, and o-cresol, in a 3:1 mixture with the hydrogen-bond acceptor choline chloride. Density, viscosity, and pulsed-field gradient NMR diffusivity measurements were conducted over a range of temperatures. Classical and ab initio molecular dynamics simulation results match experimental data reasonably well. Furthermore, the simulation results were then used to perform a more detailed analysis of the local structure and dynamics of these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Unconventional polaronic ground state in superconducting LiTi 2 O 4

Geometrically frustrated lattices can display a range of correlated phenomena, ranging from spin frustration and charge order to dispersionless flat bands due to quantum interference. One particularly compelling family of such materials is the half-valence spinel LiB 2 O 4 materials. On the B-site frustrated pyrochlore sublattice, the interplay of correlated metallic behavior and charge frustration leads to a superconducting state in LiTi 2 O 4 and heavy fermion behavior in LiV 2 O 4 . To date, however, LiTi 2 O 4 has primarily been understood as a conventional BCS superconductor despite a lattice structure that could host more exotic ground states. Here, we present a multimodal investigation of LiTi 2 O 4 , combining ARPES, RIXS, proximate magnetic probes, and ab-initio many-body theoretical calculations. Our data reveals a novel mobile polaronic ground state with spectroscopic signatures that underlie co-dominant electron-phonon coupling and electron-electron correlations also found in the lightly doped cuprates. The cooperation between the two interaction scales distinguishes LiTi 2 O 4 from other superconducting titanates, suggesting an unconventional origin to superconductivity in LiTi 2 O 4 . Our work deepens our understanding of the rare interplay of electron-electron correlations and electron-phonon coupling in unconventional superconducting systems. In particular, our work identifies the geometrically frustrated, mixed-valence spinel family as an under-explored platform for discovering unconventional, correlated ground states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strong-field induced fragmentation and isomerization of toluene probed by ultrafast femtosecond electron diffraction and mass spectrometry

We investigate the fragmentation and isomerization of toluene molecules induced by strong-field ionization with a femtosecond near-infrared laser pulse. Momentum-resolved coincidence time-of-flight ion mass spectrometry is used to determine the relative yield of different ionic products and fragmentation channels as a function of laser intensity. Ultrafast electron diffraction is used to capture the structure of the ions formed on a picosecond time scale by comparing the diffraction signal with theoretical predictions. Through the combination of the two measurements and theory, we are able to determine the main fragmentation channels and to distinguish between ions with identical mass but different structures. In addition, our diffraction measurements show that the independent atom model, which is widely used to analyze electron diffraction patterns, is not a good approximation for diffraction from ions. Here, we show that the diffraction data is in very good agreement with ab initio scattering calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Optical conductivity of layered topological semimetal TaNiTe 5

Here, we present an infrared spectroscopy study of the layered topological semimetal TaNiTe 5 , a material with a quasi-one-dimensional structure and strong in-plane anisotropy. Despite its structural features, infrared reflectivity and electronic transport measurements along the 𝑎 and 𝑐 crystallographic axes show metallic behavior without evidence of reduced dimensionality. Optical conductivity reveals an anisotropic but conventional metallic response with low scattering rates and a single sharp infrared-active phonon mode at 396cm −1 ⁢(49meV). Ab initio calculations closely match the experimental optical data and confirm a three-dimensional electronic structure. Our results demonstrate that TaNiTe 5 behaves as a three-dimensional anisotropic semimetal in its electronic and optical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Temperature-induced structural evolution in liquid Ag-Ga alloys

Temperature-dependent atomic structural evolutions of liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys have been studied by in situ high-energy x-ray-diffraction (HEXRD) experiments combined with ab initio molecular-dynamics simulations. The experimental data show a reversible structural crossover at about 1050 ~ 1100 (± 50) K in both liquid Ag 60 Ga 40 and Ag 70 Ga 30 alloys. Obvious changes of the electrical resistivity, absolute thermoelectric power, and atomic diffusivity around the similar temperature range for both Ag-Ga liquids strongly support the HEXRD results. The origin of the liquid-to-liquid crossover in both Ag-Ga liquids was suggested to link with the rearrangements of Ag and Ga atoms, i.e., Ag and Ga atoms prefer to associate with themselves in the higher temperature range above 1100 K, consistent with the accelerated increase of the strong covalently bonded Ga–Ga dimers in both Ag-Ga liquids. In addition, more studies from the energy aspect are still desirable to understand the rearrangements of Ag and Ga atoms in the higher temperature range in both Ag-Ga liquids.

36 MATERIALS SCIENCE↗